30 resultados para Atributos de produto


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The aim of the present study was to extract vegetable oil from brown linseed (Linum usitatissimum L.), determine fatty acid levels, the antioxidant capacity of the extracted oil and perform a rapid economic assessment of the SFE process in the manufacture of oil. The experiments were conducted in a test bench extractor capable of operating with carbon dioxide and co-solvents, obeying 23 factorial planning with central point in triplicate, and having process yield as response variable and pressure, temperature and percentage of cosolvent as independent variables. The yield (mass of extracted oil/mass of raw material used) ranged from 2.2% to 28.8%, with the best results obtained at 250 bar and 50ºC, using 5% (v/v) ethanol co-solvent. The influence of the variables on extraction kinetics and on the composition of the linseed oil obtained was investigated. The extraction kinetic curves obtained were based on different mathematical models available in the literature. The Martínez et al. (2003) model and the Simple Single Plate (SSP) model discussed by Gaspar et al. (2003) represented the experimental data with the lowest mean square errors (MSE). A manufacturing cost of US$17.85/kgoil was estimated for the production of linseed oil using TECANALYSIS software and the Rosa and Meireles method (2005). To establish comparisons with SFE, conventional extraction tests were conducted with a Soxhlet device using petroleum ether. These tests obtained mean yields of 35.2% for an extraction time of 5h. All the oil samples were sterilized and characterized in terms of their composition in fatty acids (FA) using gas chromatography. The main fatty acids detected were: palmitic (C16:0), stearic (C18:0), oleic (C18:1), linoleic (C18:2n-6) and α-linolenic (C18:3n-3). The FA contents obtained with Soxhlet dif ered from those obtained with SFE, with higher percentages of saturated and monounsaturated FA with the Soxhlet technique using petroleum ether. With respect to α-linolenic content (main component of linseed oil) in the samples, SFE performed better than Soxhlet extraction, obtaining percentages between 51.18% and 52.71%, whereas with Soxhlet extraction it was 47.84%. The antioxidant activity of the oil was assessed in the β-carotene/linoleic acid system. The percentages of inhibition of the oxidative process reached 22.11% for the SFE oil, but only 6.09% for commercial oil (cold pressing), suggesting that the SFE technique better preserves the phenolic compounds present in the seed, which are likely responsible for the antioxidant nature of the oil. In vitro tests with the sample displaying the best antioxidant response were conducted in rat liver homogenate to investigate the inhibition of spontaneous lipid peroxidation or autooxidation of biological tissue. Linseed oil proved to be more efficient than fish oil (used as standard) in decreasing lipid peroxidation in the liver tissue of Wistar rats, yielding similar results to those obtained with the use of BHT (synthetic antioxidant). Inhibitory capacity may be explained by the presence of phenolic compounds with antioxidant activity in the linseed oil. The results obtained indicate the need for more detailed studies, given the importance of linseed oil as one of the greatest sources of ω3 among vegetable oils

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The green bean has organoleptic and nutritional characteristics that make it an important food source in tropical regions such as the Northeast of Brazil. It is a cheap source of protein and important for nutrition of rural population contributing significantly in subsistence farming of the families from Brazil s northeast. It is consumed in entire region and together with the dry meat and other products composes the menu of typical restaurants, being characterized as an important product for economy of Northeast. The green bean is consumed freshly harvested and has short cycle, being characterized as a very perishable food, which hampers your market. The drying method is an alternative to increase the lifetime and provide a reduction volume of this product making easier your transportation and storage. However is necessary to search ways of drying which keep the product quality not only from the nutritional standpoint but also organoleptic. Some characteristics may change with the drying process such as the coloring, the rehydration capacity and the grains cooking time. The decrease of drying time or of exposure of the grains to high temperature minimizes the effects related with the product quality loss. Among the techniques used to reduce the drying time and improve some characteristics of the product, stands out the osmotic dehydration, widely used in combined processes such as the pretreatment in drying food. Currently the use of the microwaves has been considered an alternative for drying food. The microwave energy generates heat inside of materials processed and the heating is practically instantaneous, resulting in shorter processing times and product quality higher to that obtained by conventional methods. Considering the importance of the green beans for the Northeast region, the wastefulness of production due to seasonality of the crop and your high perishability, the proposal of this thesis is the study of drying grain by microwaves with and without osmotic pretreatment, focusing on the search of conditions of processes which favor the rehydration of the product preserving your organoleptic characteristics. Based on the analysis of the results of osmotic dehydration and dielectric properties was defined the operating condition to be used in pretreatment of the green bean, with osmotic concentration in saline solution containing 12,5% of sodium chloride, at 40°C for 20 minutes. The drying of green bean by microwave was performed with and without osmotic pretreatment on the optimized condition. The osmotic predehydration favored the additional drying, reducing the process time. The rehydration of dehydrated green bean with and without osmotic pretreatment was accomplished in different temperature conditions and immersion time according to a factorial design 22, with 3 repetitions at the central point. According to results the better condition was obtained with the osmotically pretreated bean and rehydrated at a temperature of 60°C for 90 minutes. Sensory analysis was performed comparing the sample of the green bean in natura and rehydrated in optimized conditions, with and without osmotic pretreatment. All samples showed a good acceptance rate regarding the analyzed attributes (appearance, texture, color, odor and taste), with all values above 70%. Is possible conclude that the drying of green bean by microwave with osmotic pretreatment is feasible both in respect to technical aspects and rehydration rates and sensory quality of the product

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Traditional applications of feature selection in areas such as data mining, machine learning and pattern recognition aim to improve the accuracy and to reduce the computational cost of the model. It is done through the removal of redundant, irrelevant or noisy data, finding a representative subset of data that reduces its dimensionality without loss of performance. With the development of research in ensemble of classifiers and the verification that this type of model has better performance than the individual models, if the base classifiers are diverse, comes a new field of application to the research of feature selection. In this new field, it is desired to find diverse subsets of features for the construction of base classifiers for the ensemble systems. This work proposes an approach that maximizes the diversity of the ensembles by selecting subsets of features using a model independent of the learning algorithm and with low computational cost. This is done using bio-inspired metaheuristics with evaluation filter-based criteria

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The objective of the researches in artificial intelligence is to qualify the computer to execute functions that are performed by humans using knowledge and reasoning. This work was developed in the area of machine learning, that it s the study branch of artificial intelligence, being related to the project and development of algorithms and techniques capable to allow the computational learning. The objective of this work is analyzing a feature selection method for ensemble systems. The proposed method is inserted into the filter approach of feature selection method, it s using the variance and Spearman correlation to rank the feature and using the reward and punishment strategies to measure the feature importance for the identification of the classes. For each ensemble, several different configuration were used, which varied from hybrid (homogeneous) to non-hybrid (heterogeneous) structures of ensemble. They were submitted to five combining methods (voting, sum, sum weight, multiLayer Perceptron and naïve Bayes) which were applied in six distinct database (real and artificial). The classifiers applied during the experiments were k- nearest neighbor, multiLayer Perceptron, naïve Bayes and decision tree. Finally, the performance of ensemble was analyzed comparatively, using none feature selection method, using a filter approach (original) feature selection method and the proposed method. To do this comparison, a statistical test was applied, which demonstrate that there was a significant improvement in the precision of the ensembles

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Classifier ensembles are systems composed of a set of individual classifiers and a combination module, which is responsible for providing the final output of the system. In the design of these systems, diversity is considered as one of the main aspects to be taken into account since there is no gain in combining identical classification methods. The ideal situation is a set of individual classifiers with uncorrelated errors. In other words, the individual classifiers should be diverse among themselves. One way of increasing diversity is to provide different datasets (patterns and/or attributes) for the individual classifiers. The diversity is increased because the individual classifiers will perform the same task (classification of the same input patterns) but they will be built using different subsets of patterns and/or attributes. The majority of the papers using feature selection for ensembles address the homogenous structures of ensemble, i.e., ensembles composed only of the same type of classifiers. In this investigation, two approaches of genetic algorithms (single and multi-objective) will be used to guide the distribution of the features among the classifiers in the context of homogenous and heterogeneous ensembles. The experiments will be divided into two phases that use a filter approach of feature selection guided by genetic algorithm

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Software Product Line (SPL) consists of a software development paradigm, whose main focus is to identify features common and variability among applications in a specific domain. An LPS is designed to attend all products requirements from its product family. These requirements and LPS may have changes over time due to several factors, such as evolution of product requirements, evolution of the market, evolution of SLP process, evolution of the technologies used to develop the products. To handle these changes, LPS should be modified and evolve in order to not become obsolete, and adapt itself to new requirements. The Changes Impact Analysis is an activity that understand and identify what consequences these changes are cause on LPS. Impact Analysis on LPS may be supported by traceability relationships, which identify relationships between artefacts created during all phases of software development. Despite the solutions of change impact analysis based on traceability for software, there is a lack of solutions for assessing the change impact analysis based on traceability for LPS, since existing solutions do not include estimates specific to the artefacts of LPS. Thus, this paper proposes a process of change impact analysis and an tool for assessing the change impact through traceability of artefacts in LPS. For this purpose, we specified a process of change impact analysis that considers artifacts produced during the development of LPS. We have also implemented a tool which allows estimating and identifying artefacts and products of LPS affected from changes in other products, changes in class, changes in features, changes between releases of LPS and artefacts related to changes in core assets and variability. Finally, the results were evaluated through metrics

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Product derivation tools are responsible for automating the development process of software product lines. The configuration knowledge, which is responsible for mapping the problem space to the solution space, plays a fundamental role on product derivation approaches. Each product derivation approach adopts different strategies and techniques to manage the existing variabilities in code assets. There is a lack of empirical studies to analyze these different approaches. This dissertation has the aim of comparing systematically automatic product derivation approaches through of the development of two different empirical studies. The studies are analyzed under two perspectives: (i) qualitative that analyzes the characteristics of approaches using specific criteria; and (ii) quantitative that quantifies specific properties of product derivation artifacts produced for the different approaches. A set of criteria and metrics are also being proposed with the aim of providing support to the qualitative and quantitative analysis. Two software product lines from the web and mobile application domains are targets of our study

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Through the adoption of the software product line (SPL) approach, several benefits are achieved when compared to the conventional development processes that are based on creating a single software system at a time. The process of developing a SPL differs from traditional software construction, since it has two essential phases: the domain engineering - when common and variables elements of the SPL are defined and implemented; and the application engineering - when one or more applications (specific products) are derived from the reuse of artifacts created in the domain engineering. The test activity is also fundamental and aims to detect defects in the artifacts produced in SPL development. However, the characteristics of an SPL bring new challenges to this activity that must be considered. Several approaches have been recently proposed for the testing process of product lines, but they have been shown limited and have only provided general guidelines. In addition, there is also a lack of tools to support the variability management and customization of automated case tests for SPLs. In this context, this dissertation has the goal of proposing a systematic approach to software product line testing. The approach offers: (i) automated SPL test strategies to be applied in the domain and application engineering, (ii) explicit guidelines to support the implementation and reuse of automated test cases at the unit, integration and system levels in domain and application engineering; and (iii) tooling support for automating the variability management and customization of test cases. The approach is evaluated through its application in a software product line for web systems. The results of this work have shown that the proposed approach can help the developers to deal with the challenges imposed by the characteristics of SPLs during the testing process

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The tracking between models of the requirements and architecture activities is a strategy that aims to prevent loss of information, reducing the gap between these two initial activities of the software life cycle. In the context of Software Product Lines (SPL), it is important to have this support, which allows the correspondence between this two activities, with management of variability. In order to address this issue, this paper presents a process of bidirectional mapping, defining transformation rules between elements of a goaloriented requirements model (described in PL-AOVgraph) and elements of an architectural description (defined in PL-AspectualACME). These mapping rules are evaluated using a case study: the GingaForAll LPS. To automate this transformation, we developed the MaRiPLA tool (Mapping Requirements to Product Line Architecture), through MDD techniques (Modeldriven Development), including Atlas Transformation Language (ATL) with specification of Ecore metamodels jointly with Xtext , a DSL definition framework, and Acceleo, a code generation tool, in Eclipse environment. Finally, the generated models are evaluated based on quality attributes such as variability, derivability, reusability, correctness, traceability, completeness, evolvability and maintainability, extracted from the CAFÉ Quality Model

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The approach Software Product Line (SPL) has become very promising these days, since it allows the production of customized systems on large scale through product families. For the modeling of these families the Features Model is being widely used, however, it is a model that has low level of detail and not may be sufficient to guide the development team of LPS. Thus, it is recommended add the Features Model to other models representing the system from other perspectives. The goals model PL-AOVgraph can assume this role complementary to the Features Model, since it has a to context oriented language of LPS's, which allows the requirements modeling in detail and identification of crosscutting concerns that may arise as result of variability. In order to insert PL-AOVgraph in development of LPS's, this paper proposes a bi-directional mapping between PL-AOVgraph and Features Model, which will be automated by tool ReqSys-MDD. This tool uses the approach of Model-Driven Development (MDD), which allows the construction of systems from high level models through successive transformations. This enables the integration of ReqSys-MDD with other tools MDD that use their output models as input to other transformations. So it is possible keep consistency among the models involved, avoiding loss of informations on transitions between stages of development

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The Exception Handling (EH) is a widely used mechanism for building robust systems. In Software Product Line (SPL) context it is not different. As EH mechanisms are embedded in most of mainstream programming languages (like Java, C# and C++), we can find exception signalers and handlers spread over code assets associated to common and variable SPL features. When exception signalers and handlers are added to an SPL in an unplanned way, one of the possible consequences is the generation of faulty family instances (i.e., instances on which common or variable features signal exceptions that are mistakenly caught inside the system). In this context, some questions arise: How exceptions flow between the optional and alternative features an LPS? Aiming at providing answers to these questions, this master thesis conducted an exploratory study, based on code inspection and static analysis code, whose goal was to categorize the main ways which exceptions flow in LPSs. To support the study, we developed an static analysis tool called PLEA (Product Line Exception Analyzer) that calculates the exceptional flows of LPSs, and categorize these flows according to the features associated with handlers and signalers. Preliminary results showed that some types of exceptional flows have more potential to yield failures in exceptional behavior of SLPs

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Software Products Lines (SPL) is a software engineering approach to developing software system families that share common features and differ in other features according to the requested software systems. The adoption of the SPL approach can promote several benefits such as cost reduction, product quality, productivity, and time to market. On the other hand, the SPL approach brings new challenges to the software evolution that must be considered. Recent research work has explored and proposed automated approaches based on code analysis and traceability techniques for change impact analysis in the context of SPL development. There are existing limitations concerning these approaches such as the customization of the analysis functionalities to address different strategies for change impact analysis, and the change impact analysis of fine-grained variability. This dissertation proposes a change impact analysis tool for SPL development, called Squid Impact Analyzer. The tool allows the implementation of change impact analysis based on information from variability modeling, mapping of variability to code assets, and existing dependency relationships between code assets. An assessment of the tool is conducted through an experiment that compare the change impact analysis results provided by the tool with real changes applied to several evolution releases from a SPL for media management in mobile devices

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Being available as a tourist destination is a necessary condition but not enough for the expansion and success of tourism activity. To be successful, tourism requires investment, inputs, appropriate planning and management, like any other economic activity. A fundamental goal of the destination management is to understand how the competitiveness of a tourist destination can be improved and sustained. Competitive position of tourism can be measured and assessed by various models. Evaluating the indicators of competitiveness of a tourist destination involves a multivariate analysis, ranging from issues directly related to tourism activity itself to the indirect factors. These are elements that are interrelated and that together will point out the competitive condition of this destination. From the definition and characterization of competitiveness, sustainability and management in the context of tourist destinations, understood as the main concepts of this study, we present the main theoretical and methodological models of assessment of competitiveness of tourist destinations in the literature and represent the state of the issue in the scientific treatment of the subject. These models, designed by researchers from several countries and applied in different tourist destinations, are confronted about their structure, indicators considered and localities in which they were applied. The aim of this study was to know and evaluate the condition of tourist competitiveness of the destination Pólo Costa das Dunas, from the constraints attributes of superior performance of the evaluation model of tourist competitiveness of destinations Competenible, suggested by Mazaro, and that suit the requirements of international market aware of the strength and importance of sustainability. The condition of competitiveness of tourist destination in Rio Grande do Norte Pólo Costa das Dunas was moderate. The competitive strengths and weaknesses of the destination Pólo Costa das Dunas revealed through the dozens of sustainable attributes of the model Competenible showed guidelines and initiatives that can be taken to guide strategic decisions related to their planning and management. Thus, this study should serve as support for strategic planning and long-term management of the sector and as a crucial tool for making decisions related to public policies, sectoral investments, monitor processes, strategic planning, direction and control of the local and regional tourism development of destinations

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In production lines, the entire process is bound to unexpected happenings which may cost losing the production quality. Thus, it means losses to the manufacturer. Identify such causes and remove them is the task of the processing management. The on-line control system consists of periodic inspection of every month produced item. Once any of those items is quali ed as not t, it is admitted that a change in the fraction of the items occurred, and then the process is stopped for adjustments. This work is an extension of Quinino & Ho (2010) and has as objective main to make the monitoramento in a process through the control on-line of quality for the number of non-conformities about the inspected item. The strategy of decision to verify if the process is under control, is directly associated to the limits of the graphic control of non-conformities of the process. A policy of preventive adjustments is incorporated in order to enlarge the conforming fraction of the process. With the help of the R software, a sensibility analysis of the proposed model is done showing in which situations it is most interesting to execute the preventive adjustment

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The main objective of the present thesis was the seismic interpretation and seismic attribute analysis of the 3D seismic data from the Siririzinho high, located in the Sergipe Sub-basin (southern portion of Sergipe-Alagoas Basin). This study has enabled a better understanding of the stratigraphy and structure that the Siririzinho high experienced during its development. In a first analysis, we used two types of filters: the dip-steered median filter, was used to remove random noise and increase the lateral continuity of reflections, and fault-enhancement filter was applied to enhance the reflection discontinuities. After this filtering step similarity and curvature attributes were applied in order to identify and enhance the distribution of faults and fractures. The use of attributes and filtering greatly contributed to the identification and enhancement of continuity of faults. Besides the application of typical attributes (similarity and curvature) neural network and fingerprint techniques were also used, which generate meta-attributes, also aiming to highlight the faults; however, the results were not satisfactory. In a subsequent step, well log and seismic data analysis were performed, which allowed the understanding of the distribution and arrangement of sequences that occur in the Siririzinho high, as well as an understanding of how these units are affected by main structures in the region. The Siririzinho high comprises an elongated structure elongated in the NS direction, capped by four seismo-sequences (informally named, from bottom to top, the sequences I to IV, plus the top of the basement). It was possible to recognize the main NS-oriented faults, which especially affect the sequences I and II, and faults oriented NE-SW, that reach the younger sequences, III and IV. Finally, with the interpretation of seismic horizons corresponding to each of these sequences, it was possible to define a better understanding of geometry, deposition and structural relations in the area.